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The Impact of AI on Modern Marketing

Overview

The modern marketer has a single-most, overarching and critical objective: to deliver the right message at the right time to the right audience, efficiently.

This holy grail for most marketers isn’t just a lofty goal, it’s unobtanium—where the most we dare hope is to learn a few things during our quest for it.

Or at least that’s what I thought before I heard from 70 marketing executives, practitioners and AI enthusiasts who provided their insights on the future of AI, as it relates to marketing.

It’s not about what we see in Westworld or Skynet or even Joshua (of 1983 WarGames). And it’s not about taking the jobs of humans. Instead, the future of AI promises marketers an opportunity to connect with customers, in a personal way, with speed and precision.

Demystifying AI

For some marketers, expert definitions and explanations of artificial intelligence are a jumbled heap of big words and concepts.

As a marketer, it’s important to stay focused on the “what” and avoid getting bogged down by the “how,” especially for those who may feel intimidated by technology.

So here's my stab at simplifying AI for the non-technical marketer:

  • Artificial intelligence, or AI, is human intelligence shown by machines.
  • To achieve AI, machines are programmed to learn using formulas and complicated math. This is machine learning.
  • Then, machines play a “what if?” game, going through many variables, faster than humanly possible, without taking a break. It’s always learning. This is deep learning.

Who should read this?

Growing up, my dad would say, "If you have a hammer, all you see are nails."

And similarly, "Don't hammer a nail with a monkey wrench."

A marketer's competitive advantage is often their ability to find and use the right tools for the job. But with the marketing technology landscape of solutions exploding (now over 5,000 solutions strong), keeping up is a struggle. And that struggle is real.

Marketing executives, technologists, practitioners and anyone who is involved in the customer journey should read this report.  It's broken into four parts:

  1. The Impact of AI on Modern Marketing, Part I: Marketing Technology (martech) Meets AI
  2. The Impact of AI on Modern Marketing, Part II: How AI Promises to Deliver the Right Message at the Right Time to the Right Audience, Efficiently
  3. The Impact of AI on Modern Marketing, Part III: Scoring AI's Impact on Marketing Technology with Comments from Experts
  4. The Impact of AI on Modern Marketing, Part IV: 13 Realistic AI Outcomes Marketers Can Expect


The Impact of AI on Modern Marketing, Part I

Marketing technology (martech) meets AI

According to an IBM report, 73 percent of CEOs say cognitive computing, or AI, will play an important role in the future of their organizations.

And, according to Gartner’s emerging technologies hype cycle, we’re still at the “Peak of Inflated Expectations;” with machine learning a few years away from mainstream adoption.

Source: Gartner (July 2017)

However, when we look at martech (solutions focused on helping marketers connect with customers) we’re much deeper into the cycle. AI is already a key component in many martech solutions and promises to evolve exponentially along with the martech landscape.

A few AI terms and definitions from a martech perspective

By no means is this a comprehensive list of AI terms, but rather just a few of the core terms you should understand as a marketer.

Machine learning, a set of algorithms used by intelligent systems that learn from experience, is an approach to AI that gives marketers the means to take huge amounts of data to build target audiences, personalize messaging and leapfrog potential buyers in their customer journey.

Martech will be getting a big boost from machine learning. The capacity to process a lot of unstructured data will reap massive marketing rewards previously difficult to obtain by marketing professionals themselves. — Kristoffer Nelson, COO at SRAX

Every marketer needs to get smarter about the impact of AI, machine learning, and robots (three different things) on his marketing function and every marketing executive needs to invest in the RIGHT technologies and not just jump on a solution because it has AI in its sales pitch.  — Nancy A. Shenker, Founder at theONswitch marketing

Natural language processing, or NLP, based on machine learning algorithms, is how computers derive meaning from human language.

Real-world applications include automatic text summarization, sentiment analysis, topic extraction, named entity recognition, parts-of-speech tagging, relationship extraction, stemming, text mining, machine translation, and automated question answering. But the future of AI in marketing promises so much more.

Not an AI engineer? No problem. Built-in NLP is a simple way for developers to incorporate NLP into their bots. When enabled, built-in NLP automatically detects meaning and information in a user's message text before being passed to the bot. — Kemal Moujahid, Product Lead at Facebook Messenger

A number of organisations will commence their AI journey through chatbots. While a small number of organisations currently use them just to answer basic questions, we will see more use of them to not only start the sales process, but also take the customer on the complete buying journey through to the final purchase transaction. Only a small number of organisations have taken bots through to this extent currently. — Steve de Mamiel, Director at Hostopia

Influencer marketing may see the greatest impact of artificial intelligence in language processing and image recognition technologies. Both processes analyze conversations and pictures across the social web, like those on Instagram, YouTube, Facebook, and Twitter. And from these conversations, the technology learns the user's interests, their expertise, and later on, their true influence on their audience. — Yuval Maoz, Head of Marketing at Klear

Deep learning is a method, or technique, to achieve machine learning. Differentiated from task-specific learning, think of deep learning as uncovering layers upon layers of intelligence where the higher layers provide explanation and the lower, or deeper layers, provide more abstract concepts.

The deep learning approach engages machines to find relationships between data points, not previously considered, taking us far beyond the handful of demographic or user behaviour. Deep learning helps us build models that contain hundreds of variables with a noticeable impact on the outcome. — Mark Cook, Digital Marketing Director at ApplinSkinner

Artificial Intelligence is achieved when a machine exhibits cognitive behavior without being explicitly told to do so. Many marketers want to achieve AI autonomy, but don't have enough data to properly train a model to make accurate predictions.  — Ran Craycraft, Managing Partner at Wildebeest

Recommender systems, like those on ecommerce sites, use deep learning to build relationships and get to know the customer with every interaction, both on and off the site, penetrating each layer to provide more accurate recommendations, personalized content and even offers.

If you’ve ever taken an IQ test, you know that your ability to recognize patterns weighs heavily on the results. “Humans are amazing pattern-recognition machines and the ability to transform recursive probabilistic fractals” into concrete, actionable steps is what sets us apart from machines.1

Artificial neural networks, inspired by biological neural networks, close this gap.

(Neural networks) allow the marketing team to identify patterns in behaviour or interactions that might otherwise be overlooked without the AI application. For example, the AI application might start to recognise purchasing patterns based on where someone is from or what interests they have indicated. — Steve de Mamiel, Director at Hostopia



And all roads lead back to data. Our ability to efficiently collect and process large amounts of data has improved. In fact, last year a report found that 90 percent of the data in the world today has been created in the last two years alone, at 2.5 quintillion bytes of data per day.

People can only process a limited amount of information, and Big Data presented an impossible challenge of processing all data and filtering only useful information. This is the huge gap that AI bridges. — Jonathan Cherki, CEO at ContentSquare

The capacity to process a lot of unstructured data will reap massive marketing rewards previously difficult to obtain by marketing professionals themselves. — Kristoffer Nelson, COO at SRAX

Like 97% of influencers , I believe AI is the future of marketing, an incredibly data-heavy space. Tomorrow's smart automation will unlock the power of data with unprecedented granularity and precision. — Chaitanya Chandrasekar, Co-founder and CEO at QuanticMind

With massive amounts of data, measurements and algorithms to support its growth, AI is now finally in a stage where it can solve real-world specific problems much better than humans can across many domains. —  Michael Green, Chief Analytics Officer at Blackwood Seven


The Impact of AI on Modern Marketing, Part II:

How AI promises to deliver the right message at the right time to the right audience, efficiently

There are a multitude of frameworks and visualizations to help marketers map the buyer’s journey. And irrespective of the framework you use, the reason we map this journey is to achieve the ultimate culminating goals:

  • convert visitors to loyal customers and
  • generate lots of revenue.

In order to do this, we look at where the prospective buyer is in the journey and determine the message that will resonate most, given what we know about them.

In the future, Artificial Intelligence will help marketers better deliver the right message to the right person at the right time. Meaning, AI will help determine a consumer's interests or pain points and craft a message that directly addresses them.  — Brianna Valleskey, Marketing Consultant & Founder at Brave Ink

And while some are skeptical about how this will impact the user experience...

Every new way to deliver "the right ad to the right person at the right time"— which is what AI will do—is just a new type of annoying direct response campaigns. — Samuel Scott, Global Marketing Speaker | Columnist, The Drum

Marketers are optimistic that AI will help move the needle in terms of delivering

  • the right message,
  • at the right time,
  • to the right audience,
  • efficiently.


The right message

Based on what you know about your prospective buyer (i.e. previous behavior, demographics, content consumed, etc.), what is the most effective message or offer you can make to move them further down their journey?



This is the premise of delivering the “right message.” The right message isn’t only what you say, but also in the format of the message (i.e. paper, infographic, email, social media post, coupon, etc.) and what you have to offer.

The next frontier in marketing is upon us, and it’s characterized by the robust use of AI and machine learning to finally nail the age old problem of sending people marketing messages that they are truly happy to receive. — Dana Gibber, COO at Headliner Labs

Using AI to optimize the very words marketers use to connect with audiences in a meaningful way will help brands create a solid foundation for rewarding relationships, for both parties, now and well into the future. — Assaf Baciu, SVP of Product & Engineering and Co-Founder at Persado

[Users will] eventually be getting hyper-targeted, showing you the right ads before you have the need. — Erik Harbison, CMO at AWeber

Using automated machine learning marketers will enable highly relevant content and offers. AI/ML allows for each section of a page or email to be customized per individual. As close to 1:1 as it gets. — Ned Cullen, North America Analytics discipline leader at IBM


The right time

What if all of your prospective buyers told you directly when they were ready to take the next step in their journey towards becoming a customer?

That marketer’s utopia doesn’t exist yet. But AI has the potential to achieve the same outcome through interpretation and prediction.

One of the many benefits of using such technology would be the ability to harness intelligence from a variety of data sources, such as weather forecasts, local traffic information, local events, user activities, and more to predict the best time to air an advertorial, for instance. In other words, it will become an essential part of marketing machinery. — Nabeel Khalid, Marketing Manager at Crozdesk

There are already programs using AI that let marketers do predictive analytics and see the likelihood of a visitor to become a customer. These programs will allow marketers to better determine where their initiatives are spent best in regards to projected sales. — Lindsey Havens, Senior Marketing Manager at PhishLabs


The right audience

Buyer personas are essentially what we, as marketers, believe to be our ideal customers.

But are they?



We make assumptions about who will buy our stuff, but AI can help us validate whether we are correct about our assumptions and help us determine new target audiences we may have never considered.

Armed with the data that AI can provide, marketers will cast a significantly smaller net for lead gen, because they’ll undoubtedly know where to find their target audience. As a result, brand awareness will become less about broadcasting information to anyone who will listen, and more about engaging with relevant consumers to show how a brand can provide something they’re already looking for. — Jason Flaks, Senior Director of Product and Engineering, Speech Analytics at Marchex

Tomorrow, there is no need to waste 50% of advertising budget, because we will know who is interested in our messaging and we will pay them to listen. AI will tell us who we need to talk to, when and how with what message and information. — Mark Mueller-Eberstein, CEO & Founder at Adgetec

Clustering algorithms enable extremely accurate customer segmentation by detecting clusters of similarity in multidimensional space where each customer attribute (age, sex, income, location, purchase history, etc) represents an additional dimension. — Jay Speidell, Sales and Marketing Coordinator at Momentum


Efficiently

There’s a phrase for those who provide services, “You can have it fast, right or cheap. Pick 2.”



AI defies this true, albeit snarky, adage.

While efficiency isn’t quite the new revenue, improving business workflows by finding ways to do marketing faster and better will sequentially make things cheaper.

But this isn’t the biggest benefit we see from improved efficiency. A better customer experience tops the list of the impact AI will make in the past, present and future as it relates to marketing.

With AI, we’ll be able to allow campaigns to create and run themselves, with ideas based on its analysis of current affairs and trends. — Laura Hall, Marketing Executive at Shiply

It's almost impossible to program a machine to do (certain) tasks on a classical 'decision tree' style basis, but recent advances in AI, specifically machine learning, have given us the ability to make machines efficient at these tasks—frighteningly efficient. — Mark Cook, Digital Marketing Director at ApplinSkinner

The ability to deliver the right message at the right time to the right audience is a marketer’s holy grail. AI has the full potential, in a few short years, to achieve this through various martech applications via marketing tactics and strategies.

Next: The Impact of AI on Modern Marketing, Part III: Scoring AI's Impact on Marketing Technology with Comments from Experts


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Also in this series:

The Impact of AI on Modern Marketing, Part I: Marketing Technology (martech) Meets AI

The Impact of AI on Modern Marketing, Part II: How AI Promises to Deliver the Right Message at the Right Time to the Right Audience, Efficiently

The Impact of AI on Modern Marketing, Part III: Scoring AI's Impact on Marketing Technology with Comments from Experts

The Impact of AI on Modern Marketing, Part IV: 13 Realistic AI Outcomes Marketers Can Expect


A special thanks to our contributors:

Dean Abbott, Chief Data Scientist at SmarterHQ | Assaf Baciu, SVP of Product and Co-Founder at Persado | Jake Bennett, CTO at POP | Claudine Bianchi, CMO at ClickSoftware | Alexandra Bohigian, Marketing Coordinator at Enola Labs | Jordan Brannon, President at Coalition Technologies | Sanjay Castelino, VP of Marketing at Spiceworks | Chaitanya Chandrasekar, Co-founder and CEO at QuanticMind | Sid Chaudhary, Founder at Intempt Technologies | Derek Cheng, Director of Content Marketing at Tipalti | Jonathan Cherki, CEO at ContentSquare | Joe Chernov, Vice President of Marketing at InsightSquared | Mark Cook, Digital Marketing Director at ApplinSkinner | Ran Craycraft, Managing Partner at Wildebeest | Ned Cullen, North America Analytics discipline leader at IBM | Mahi de Silva, CEO at Botworx.ai | Sandra Fathi, Founder and CEO at Affect | Adam Fingerman , Chief Experience Officer and Co-Founder at ArcTouch | Jason Flaks, Senior Director of Product and Engineering, Speech Analytics at Marchex | Dana Gibber, COO at Headliner Labs | Michael Green, Chief Analytics Officer at Blackwood Seven | Louis Gudema, President at revenue + associates | Laura Hall, Marketing Executive at Shiply | Erik Harbison, CMO at AWeber | Lindsey Havens, Senior Marketing Manager at PhishLabs | Michelle Huff, CMO at Act-On Software | Suraj Kandukuri, Marketing Lead at Preferred Surgicenter | Stephane Kasriel, CEO at Upwork | Jitesh Keswani, CEO at e-intelligence | Nabeel Khalid, Marketing Manager at Crozdesk | Ian Khan, Technology Futurist at IanKhan.com | John Koetsier, trend watcher and Mobile Economist at TUNE | Mark Kovscek, President at Velocidi | Jaroslaw Krolewski, CEO at Synerise | Jason Lavis, Marketing Director at Out of the Box Innovations Ltd. | Megan Lueders, VP of Marketing at Zenoss | Michael Litt, Co-founder & CEO of Vidyard | Steve de Mamiel , Director at Hostopia | Yuval Maoz, Head of Marketing at Klear | Karl Mattson , Senior Vice President of Growth at Fillr | Lauren Mead, CMO at TimeTrade | Etienne Mérineau, Co-Founder at Heyday.ai | Dustin Montgomery, Digital Marketing Specialist at Shippers Supplies | Kemal Moujahid, Product Lead at Facebook Messenger | Mark Mueller-Eberstein , CEO & Founder at Adgetec | Janet Muto, President and Co-Founder at WEVO | Mihir Nanavati, SVP Product & Marketing at Kahuna | Kristoffer Nelson, COO at SRAX | Ksenia Newton, Digital Marketing Manager at CrossCap | Eddie Offermann, Creative Technology Director at Mirada Studio | Carlos Rodrigo Paravella Montagner, IT Executive and Partner at Merial Animal Health | Glenn Pingul, VP of Scientific Marketing Strategies at Amplero | Brie Pinnow, CEO at Blinc Digital Group | Leah Pope, Chief Marketing Officer at Datorama, Inc. | Samaneh Pourjalali, VP, Head of Product at starbutter AI | Jake Rheude, Director of Marketing at Red Stag Fulfillment | Rob Ristagno, CEO at The Sterling Woods Group | Samuel Scott, Global Marketing Speaker and Columnist at the Drum | Nancy A Shenker, Founder at theONswitch marketing | Jay Speidell, Sales and Marketing Coordinator at Momentum | Vishal Srivastava, Director at Trainedge Consulting | Joe Staples, CMO at Workfront | Merijn te Booij, Chief Marketing Officer at Genesys | Brianna Valleskey, Marketing consultant and founder at Brave Ink | Serge Vartanov, Chief Marketing Officer at AutoGravity | Kar Villard, Manager at Neuroplanner | Rob Weatherhead, Digital Marketing and Advertising Consultant | Dariusz Zabrzenski, Head of Research and Development at LiveChat